Description
The Reinforcement Learning Conference (RLC) is dedicated to fostering collaboration and knowledge sharing among researchers in the field of reinforcement learning. Scheduled for August 15th to 18th, 2026, RLC 2026 will be held at the Jean-Brilliant Building, University of Montreal, in Montréal, QC, Canada. This conference aims to provide a more intimate setting compared to larger machine learning venues, allowing for in-depth discussions and interactions among attendees.
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RLC serves as a platform for researchers to present their work, which is subsequently published in the associated Reinforcement Learning Journal (RLJ). The RLJ is an independent, peer-reviewed journal that acts as a primary source of scholarly articles in the field. By presenting their findings at RLC, authors can enhance the reach and impact of their research, fostering a deeper understanding of their contributions.
The conference will feature a variety of sessions, including keynote speeches from leading experts in reinforcement learning, paper presentations, and networking opportunities. The event is designed to cater to a diverse audience, including academic researchers, industry professionals, and students interested in the latest advancements in reinforcement learning.
Key dates for RLC 2026 include the opening of submissions on February 17, with abstract deadlines on March 1 and paper deadlines on March 5. Decision notifications will be sent out by May 5 or May 8, ensuring that participants have ample time to prepare for the conference.
RLC 2026 is part of a broader initiative to expand the conference's reach, with future events planned in different locations. The organizers are committed to creating an inclusive environment that encourages participation from researchers worldwide, particularly those who may have faced challenges in attending previous events due to travel restrictions. This commitment to accessibility and collaboration is central to the mission of RLC, making it a must-attend event for anyone involved in reinforcement learning research.
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Highlights
Peer-reviewed publication in RLJ
Keynote speakers from industry and academia
Networking opportunities
Focused sessions on reinforcement learning
In-depth discussions
International participation
Diverse audience engagement
Research presentations
Who Should Attend
- Research Presentation
- Networking
- Knowledge Sharing
- Collaboration Opportunities
- Professional Development
